BEGIN:VCALENDAR VERSION:2.0 PRODID:-//CERN//INDICO//EN BEGIN:VEVENT SUMMARY:Use of Sub-Weekly Updated Satellite Imagery for Assessment of Dama ge - A Short Course on Earth Observation Methods and Data DTSTART;VALUE=DATE-TIME:20210623T095000Z DTEND;VALUE=DATE-TIME:20210623T104000Z DTSTAMP;VALUE=DATE-TIME:20260516T120628Z UID:indico-contribution-20-60@conferences.famnit.upr.si DESCRIPTION:Speakers: Marko Repše (Sentinel Hub)\nIn recent years the Ea rth Observation (EO) sector is going through a revolution due to data volu me and quality growth\, a significant part of which is available as open d ata. The European Copernicus mission provides new data covering the globe every 1-5 days\, including multi-spectral imaging and synthetic aperture r adar data. This provides unprecedented insight into the Earth and is also useful for assessing damage due to floods and drought\, hail and other ext reme weather events. For every event\, one can get data about the immediat e aftermath and the data prior\, making it possible to estimate the state of the ground before and recovery afterwards. We will guide users through the basics of EO data and demonstrate how they can easily access the data. This will be followed by examples and conclude with a brief introduction to how advanced machine-learning models can be used to analyse the data on a large scale.\n\n\n\nhttps://apps.sentinel-hub.com/sentinel-playground/\ nhttps://apps.sentinel-hub.com/eo-browser/\nhttps://apps.sentinel-hub.com/ requests-builder/\nhttps://www.indexdatabase.de/\nhttps://custom-scripts.s entinel-hub.com/\nhttps://www.sentinel-hub.com/explore/education/\nhttps:/ /www.sentinel-hub.com/develop/community/contest/#urban-growth-in-africa\nh ttps://race.esa.int/\nhttps://sentinelhub-py.readthedocs.io/en/latest/inde x.html\nhttps://eo-learn.readthedocs.io/en/latest/index.html\nhttps://gith ub.com/sentinel-hub/eo-learn-workshop\nhttps://github.com/sentinel-hub/eo- flow\n\nhttps://conferences.famnit.upr.si/event/20/contributions/60/ LOCATION: URL:https://conferences.famnit.upr.si/event/20/contributions/60/ END:VEVENT BEGIN:VEVENT SUMMARY:Optimization of reinsurance DTSTART;VALUE=DATE-TIME:20210623T120000Z DTEND;VALUE=DATE-TIME:20210623T125000Z DTSTAMP;VALUE=DATE-TIME:20260516T120628Z UID:indico-contribution-20-58@conferences.famnit.upr.si DESCRIPTION:Speakers: Bor Harej (Prime Re Solutions)\nReinsurance is a key risk mitigation tool\, particularly in general insurance. An insurer will cede some profit to a reinsurer to reduce the risk of its insurance resul t and make insurance results more stable. Different types of reinsurance c an be used for different insurance segments. For each reinsurance\, the in surer needs the type of reinsurance to decide how much of the risk will be transferred. Reinsurance optimization is a procedure that tries to find o ptimal reinsurance structure for each insurance segment so that the optima l balance between the cost and risk transfer is achieved and the expected total insurance result volatility is within the company risk limits.\n\nht tps://conferences.famnit.upr.si/event/20/contributions/58/ LOCATION: URL:https://conferences.famnit.upr.si/event/20/contributions/58/ END:VEVENT BEGIN:VEVENT SUMMARY:The role of knowledge graphs in insurance DTSTART;VALUE=DATE-TIME:20210623T142000Z DTEND;VALUE=DATE-TIME:20210623T151000Z DTSTAMP;VALUE=DATE-TIME:20260516T120628Z UID:indico-contribution-20-57@conferences.famnit.upr.si DESCRIPTION:Speakers: Diego Klabjan (Northwestern university)\nIn the lec ture\, we present knowledge graphs in insurance and the algorithms on how to build them\, algorithms to inferring missing facts. We focus on healthc are-related knowledge graphs occurring in insurance.\n\nhttps://conference s.famnit.upr.si/event/20/contributions/57/ LOCATION: URL:https://conferences.famnit.upr.si/event/20/contributions/57/ END:VEVENT BEGIN:VEVENT SUMMARY:Implementing data science in insurance DTSTART;VALUE=DATE-TIME:20210623T111000Z DTEND;VALUE=DATE-TIME:20210623T120000Z DTSTAMP;VALUE=DATE-TIME:20260516T120628Z UID:indico-contribution-20-56@conferences.famnit.upr.si DESCRIPTION:Speakers: Iztok Šerbec (In516ht )\nReal-life examples of ins urance companies and their path of implementing data science in their busi ness. Where they began and which business problems they covered\, and what are future challenges and opportunities that will give them an advantage in the market. Why the path was hard and slow and what has changed in rece nt years will be covered.\n\nhttps://conferences.famnit.upr.si/event/20/co ntributions/56/ LOCATION: URL:https://conferences.famnit.upr.si/event/20/contributions/56/ END:VEVENT BEGIN:VEVENT SUMMARY:How to model and implement a centralized data warehouse to spend m ore time on analyzing data than gathering it? DTSTART;VALUE=DATE-TIME:20210623T090000Z DTEND;VALUE=DATE-TIME:20210623T095000Z DTSTAMP;VALUE=DATE-TIME:20260516T120628Z UID:indico-contribution-20-54@conferences.famnit.upr.si DESCRIPTION:Speakers: Grega Jerkič (In516ht)\nMost of the teams that foc us on data-intensive work (analytics\, modelling\, optimization\, etc.) st ill spend most of the work on data preparation and data cleaning. On the o ther hand\, there is a huge spike in the number of new cloud applications that organizations use to manage their business. Because of all this\, the need for data integration and a holistic view of all data is even more cr ucial for managing the business. The presentation will focus on different possibilities of how to model the data warehouse (dimensional\, anchor\, 3 NF form) and how the whole implementation process looks like. With over 15 years of experience building complex data warehouses in financial institu tions\, we will share some of the best practices\, things we learned the h ard way\, and future trends.\n\nhttps://conferences.famnit.upr.si/event/20 /contributions/54/ LOCATION: URL:https://conferences.famnit.upr.si/event/20/contributions/54/ END:VEVENT END:VCALENDAR